Export Vitally to BigQuery

Build a comprehensive customer success data warehouse with the Vitally to BigQuery integration by Coupler.io. Centralize account health metrics, user engagement patterns, and team activities in scalable cloud infrastructure that handles growing data volumes while supporting advanced SQL analytics and machine learning applications for predictive churn modeling.

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What data you can export from Vitally?

... and many more

All-in-one tool for Vitally data exports and analytics

Consolidate customer success data from Vitally with sales pipeline information, product telemetry, and support ticket histories in your BigQuery warehouse. Build a unified data foundation where health scores, revenue events, feature usage, and service interactions combine to create complete customer journey analytics.

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Structure your customer success records into optimized BigQuery tables designed for analytical queries. Accounts, conversations, tasks, and user activities arrive organized for efficient querying, letting your data team run complex analyses without restructuring or cleaning imported data.

Organize raw Vitally data in the form of a ready-to-use data set image

Maintain an accurate customer success warehouse with scheduled exports running from every 15 minutes to monthly intervals. Your BigQuery tables stay synchronized with Vitally's latest health scores, engagement data, and team activities, supporting both real-time operational dashboards and historical trend analysis.

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Enable AI integrations that connect to your customer success data warehouse for conversational analytics. Team members across departments can ask questions about retention trends and health patterns without writing SQL, democratizing access to insights stored in BigQuery.

Connect Vitally data to AI to query and analyze data using natural language conversations image
Collect data from Vitally and enrich it with information from other sources image
Organize raw Vitally data in the form of a ready-to-use data set image
Automate data refresh on a custom schedule image
Connect Vitally data to AI to query and analyze data using natural language conversations image

Why export Vitally to BigQuery - real life cases

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Historical retention analysis

Data analysts warehouse years of customer health scores and engagement metrics to identify long-term retention patterns that aren't visible in shorter timeframes. They query how health trajectories evolved across different customer cohorts, discovering that accounts showing specific engagement patterns in months two through four have significantly higher renewal rates regardless of initial health scores.
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Cross-platform customer intelligence

Analytics teams combine Vitally's success metrics with product usage from event streams and contract data from their CRM to build comprehensive customer profiles. BigQuery's joining capabilities let them correlate which product features drive health score improvements, which engagement patterns predict expansion opportunities, and how customer success interventions impact product adoption rates.
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Predictive churn modeling at scale

Machine learning engineers export complete customer success histories to train algorithms that predict renewal likelihood months in advance. They process millions of data points across accounts, users, conversations, and tasks, testing hundreds of feature combinations to identify the earliest signals that an account might be headed toward cancellation.
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Multi-product success tracking

Companies offering multiple products warehouse Vitally data from separate workspaces into BigQuery for portfolio-level analysis. They identify customers succeeding with one product but struggling with another, spot opportunities for cross-product expansion based on health patterns, and optimize success team allocation across their entire product suite.

How to export Vitally to BigQuery

Step 1. Connect to your Vitally account and select the data to export
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Step 2. Organize data using transformation options such as filters, column management, aggregation, etc.
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Step 3. Connect your BigQuery project and specify where to load your data
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Step 4. Schedule data refresh to automate data flow from Vitally to BigQuery
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Bonus: Talk to AI about your Vitally data

Automate data exports with the no-code Vitally BigQuery integration

Quick start with dashboard templates

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No such template is available yet.
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Talk to AI about your Vitally data

Coupler.io's AI integrations let you work with Vitally data through conversational queries instead of technical tools. Connect AI to your exported customer success information and ask questions about health patterns, retention risks, and team performance using everyday language to get insights without building SQL queries or analytical models.

Examples of questions you can ask about Vitally data:
  • "What percentage of accounts that churned showed declining health scores for three consecutive months before cancellation?"
  • "How does average task completion time vary between our highest-performing success managers and the team average?"
  • "Which customer segments have the strongest relationship between conversation frequency and user adoption growth?"
  • "Among accounts that expanded in the past year, what engagement patterns did they share during their first six months?"
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Keep your data safe

Coupler.io safeguards your shared information and data transfers from breaches, leaks, and unauthorized disclosures.

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Ready to connect Vitally to BigQuery and automate your reporting?